The memristive grid outperforms the resistive grid for edge preserving smoothing

Nonlinear resistive grids have been proposed for image smoothing that preserves discontinuities. The recent development of nonlinear memristors using nanotechnology has opened the possibility for expanding the capabilities of such circuit networks by replacing the nonlinear resistors by memristors. We demonstrate here that replacing the connections between nodes in a nonlinear resistive grid with memristors yields a network that performs a similar discontinuity-preserving image smoothing, but with significant functional advantages. In particular, edges extracted from the outputs of the nonlinear memristive grid more closely match the results of human segmentations.